RawMal-TF is a new public dataset of raw Windows malware binaries labeled by 14 behavioral types and 17 families, with EMBER static features and classification benchmarks.
Data Collection and Labeling Techniques for Machine Learning
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abstract
Data collection and labeling are critical bottlenecks in the deployment of machine learning applications. With the increasing complexity and diversity of applications, the need for efficient and scalable data collection and labeling techniques has become paramount. This paper provides a review of the state-of-the-art methods in data collection, data labeling, and the improvement of existing data and models. By integrating perspectives from both the machine learning and data management communities, we aim to provide a holistic view of the current landscape and identify future research directions.
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cs.CR 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
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RawMal-TF: Raw Malware Dataset Labeled by Type and Family
RawMal-TF is a new public dataset of raw Windows malware binaries labeled by 14 behavioral types and 17 families, with EMBER static features and classification benchmarks.